System and method for processing network data

ABSTRACT

Methods and systems for providing data analytics and generating real-time and historical views of network events using a single processing pipeline, managed by a single code base, are presented. A computing device may receive a stream of data indicative of a plurality of events occurring on a network. The computing device may process the stream of data to generate intermediate data and batch data using the single processing pipeline. The intermediate data may be available to generate historical views and the batch data may include a plurality of intermediate data for a time interval. The computing device may generate a historical view of the events based on a subset of intermediate data and the batch data. Finally, the computing device may provide the historical view to a processing layer to enable the computing device to respond to requests for information about the network.

FIELD

Aspects described herein generally relate to computer networking andhardware and software related thereto. More specifically, one or moreaspects described herein provide data processing of network events.

BACKGROUND

Analytic services allow users to view real-time and historical eventsthat occur on a network. Typically, these analytic services use twodifferent processing pipelines, one for providing real-time views andanother for providing historical views. To complicate matters, thereal-time view processing pipeline and the historical view processingpipeline originate from two different code bases.

SUMMARY

The following presents a simplified summary of various aspects describedherein. This summary is not an extensive overview, and is not intendedto identify required or critical elements or to delineate the scope ofthe claims. The following summary merely presents some concepts in asimplified form as an introductory prelude to the more detaileddescription provided below.

Aspects described herein are directed towards generating real-time andhistorical views of network events using a single processing pipelineand single code base. A computing device may receive a stream of dataindicative of a plurality of events occurring on a network. Thecomputing device may process the stream of data to generate intermediatedata and batch data using a single processing pipeline. The intermediatedata may be available to generate historical views. Further, theintermediate data may be displayed as a real-time event in a real-timeview. Batch data may comprise a plurality of intermediate data for atime interval. The computing device may generate a historical view ofthe events based on a subset of intermediate data and the batch data.The computing device may respond to requests for information about thenetwork, via a processing layer, based on the generated historical view.The computing device may store the intermediate data in a first memoryand cause the intermediate data to be presented as a data point in areal-time view. Additionally, the batch data may be stored in a secondmemory, such as a temporal database. The intermediate data and batchdata may be used to detect abnormal network conditions. For instance,the intermediate data may be compared to a threshold value, and when theintermediate data is greater than the threshold, an alert may begenerated that indicates the abnormal condition. Batch data may also becompared to a threshold value to detect abnormal network conditions.When network conditions are normal (i.e. below the threshold value), theintermediate data and/or the batch data may be provided to a machinelearning system to build a model of the network. In some embodiments,one or more network parameters may be adjusted when an abnormal networkcondition is detected.

Generating intermediate data and batch data using a single processingpipeline and a single code base provides better scalability than priorart systems that implement multiple code bases and multiple processingpipelines. In particular, the single processing pipeline and single codebase reduces the consumption of processing resources and networkbandwidth resources when compared to prior art systems that implementmultiple code bases and multiple processing pipelines.

These and additional aspects will be appreciated with the benefit of thedisclosures discussed in further detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of aspects described herein and theadvantages thereof may be acquired by referring to the followingdescription in consideration of the accompanying drawings, in which likereference numbers indicate like features, and wherein:

FIG. 1 depicts an illustrative computer system architecture that may beused in accordance with one or more illustrative aspects describedherein.

FIG. 2 depicts an illustrative remote-access system architecture thatmay be used in accordance with one or more illustrative aspectsdescribed herein.

FIG. 3 depicts an illustrative virtualized system architecture that maybe used in accordance with one or more illustrative aspects describedherein.

FIG. 4 depicts an illustrative cloud-based system architecture that maybe used in accordance with one or more illustrative aspects describedherein.

FIG. 5 depicts an illustrative enterprise mobility management system.

FIG. 6 depicts an illustrative management and analytics service that maybe used to generate real-time and historical views of network events inaccordance with one or more illustrative aspects described herein.

FIGS. 7A-7C depict an illustrative algorithm of a single processingpipeline preparing real-time and historical views of network events inaccordance with one or more illustrative aspects described herein.

FIG. 8 depicts an illustrative algorithm for generating a historicalview of network events in accordance with one or more illustrativeaspects described herein.

FIGS. 9A and 9B depict examples of real-time views according to one ormore illustrative aspects described herein.

FIGS. 10A-10C depict examples of historical views according to one ormore illustrative aspects described herein.

DETAILED DESCRIPTION

In the following description of the various embodiments, reference ismade to the accompanying drawings identified above and which form a parthereof, and in which is shown by way of illustration various embodimentsin which aspects described herein may be practiced. It is to beunderstood that other embodiments may be utilized and structural andfunctional modifications may be made without departing from the scopedescribed herein. Various aspects are capable of other embodiments andof being practiced or being carried out in various different ways.

As discussed above, typical analytic services use two differentprocessing pipelines from two different code bases. In operation, thetwo different code bases overlap in the tasks that are performed. Forexample, both code bases may read the same data multiple times. The needto perform multiple reads of the same data is inefficient, both in timeand processing power. Aside from being inefficient, having multiple codebases does not scale well. Furthermore, maintaining two different codebases becomes increasingly complex over time and can lead to performancedegradation due to discrepancies between the code bases.

To overcome limitations in the prior art described above, and toovercome other limitations that will be apparent upon reading andunderstanding the present specification, aspects described herein aredirected toward generating real-time and historical views of networkevents using a single processing pipeline managed by a single code base.A single processing pipeline, as a function of a single code base, mayprovide an advantage over prior art systems that divide the processingacross multiple pipelines and spread the functionality of thesecomponents across multiple code bases. In this regard, the singleprocessing pipeline, executed by a single code base, reduces thecomplexity of maintaining multiple code bases and presents a more costeffective solution than prior art systems. Moreover, the singleprocessing pipeline and single code base provides better scalabilitythan systems that implement multiple code bases and multiple processingpipelines.

It is to be understood that the phraseology and terminology used hereinare for the purpose of description and should not be regarded aslimiting. Rather, the phrases and terms used herein are to be giventheir broadest interpretation and meaning. The use of “including” and“comprising” and variations thereof is meant to encompass the itemslisted thereafter and equivalents thereof as well as additional itemsand equivalents thereof. The use of the terms “connected,” “coupled,”and similar terms, is meant to include both direct and indirectconnecting and coupling.

Computing Architecture

Computer software, hardware, and networks may be utilized in a varietyof different system environments, including standalone, networked,remote-access (also known as remote desktop), virtualized, and/orcloud-based environments, among others. FIG. 1 illustrates one exampleof a system architecture and data processing device that may be used toimplement one or more illustrative aspects described herein in astandalone and/or networked environment. Various network nodes 103, 105,107, and 109 may be interconnected via a wide area network (WAN) 101,such as the Internet. Other networks may also or alternatively be used,including private intranets, corporate networks, local area networks(LAN), metropolitan area networks (MAN), wireless networks, personalnetworks (PAN), and the like. Network 101 is for illustration purposesand may be replaced with fewer or additional computer networks. A localarea network 133 may have one or more of any known LAN topology and mayuse one or more of a variety of different protocols, such as Ethernet.Devices 103, 105, 107, and 109 and other devices (not shown) may beconnected to one or more of the networks via twisted pair wires, coaxialcable, fiber optics, radio waves, or other communication media.

The term “network” as used herein and depicted in the drawings refersnot only to systems in which remote storage devices are coupled togethervia one or more communication paths, but also to stand-alone devicesthat may be coupled, from time to time, to such systems that havestorage capability. Consequently, the term “network” includes not only a“physical network” but also a “content network,” which is comprised ofthe data—attributable to a single entity—which resides across allphysical networks.

The components may include data server 103, web server 105, and clientcomputers 107, 109. Data server 103 provides overall access, control andadministration of databases and control software for performing one ormore illustrative aspects describe herein. Data server 103 may beconnected to web server 105 through which users interact with and obtaindata as requested. Alternatively, data server 103 may act as a webserver itself and be directly connected to the Internet. Data server 103may be connected to web server 105 through the local area network 133,the wide area network 101 (e.g., the Internet), via direct or indirectconnection, or via some other network. Users may interact with the dataserver 103 using remote computers 107, 109, e.g., using a web browser toconnect to the data server 103 via one or more externally exposed websites hosted by web server 105. Client computers 107, 109 may be used inconcert with data server 103 to access data stored therein, or may beused for other purposes. For example, from client device 107 a user mayaccess web server 105 using an Internet browser, as is known in the art,or by executing a software application that communicates with web server105 and/or data server 103 over a computer network (such as theInternet).

Servers and applications may be combined on the same physical machines,and retain separate virtual or logical addresses, or may reside onseparate physical machines. FIG. 1 illustrates just one example of anetwork architecture that may be used, and those of skill in the artwill appreciate that the specific network architecture and dataprocessing devices used may vary, and are secondary to the functionalitythat they provide, as further described herein. For example, servicesprovided by web server 105 and data server 103 may be combined on asingle server.

Each component 103, 105, 107, 109 may be any type of known computer,server, or data processing device. Data server 103, e.g., may include aprocessor 111 controlling overall operation of the data server 103. Dataserver 103 may further include random access memory (RAM) 113, read onlymemory (ROM) 115, network interface 117, input/output interfaces 119(e.g., keyboard, mouse, display, printer, etc.), and memory 121.Input/output (I/O) 119 may include a variety of interface units anddrives for reading, writing, displaying, and/or printing data or files.Memory 121 may further store operating system software 123 forcontrolling overall operation of the data processing device 103, controllogic 125 for instructing data server 103 to perform aspects describedherein, and other application software 127 providing secondary, support,and/or other functionality which may or might not be used in conjunctionwith aspects described herein. The control logic 125 may also bereferred to herein as the data server software 125. Functionality of thedata server software 125 may refer to operations or decisions madeautomatically based on rules coded into the control logic 125, mademanually by a user providing input into the system, and/or a combinationof automatic processing based on user input (e.g., queries, dataupdates, etc.).

Memory 121 may also store data used in performance of one or moreaspects described herein, including a first database 129 and a seconddatabase 131. In some embodiments, the first database 129 may includethe second database 131 (e.g., as a separate table, report, etc.). Thatis, the information can be stored in a single database, or separatedinto different logical, virtual, or physical databases, depending onsystem design. Devices 105, 107, and 109 may have similar or differentarchitecture as described with respect to device 103. Those of skill inthe art will appreciate that the functionality of data processing device103 (or device 105, 107, or 109) as described herein may be spreadacross multiple data processing devices, for example, to distributeprocessing load across multiple computers, to segregate transactionsbased on geographic location, user access level, quality of service(QoS), etc.

One or more aspects may be embodied in computer-usable or readable dataand/or computer-executable instructions, such as in one or more programmodules, executed by one or more computers or other devices as describedherein. Generally, program modules include routines, programs, objects,components, data structures, etc. that perform particular tasks orimplement particular abstract data types when executed by a processor ina computer or other device. The modules may be written in a source codeprogramming language that is subsequently compiled for execution, or maybe written in a scripting language such as (but not limited to)HyperText Markup Language (HTML) or Extensible Markup Language (XML).The computer executable instructions may be stored on a computerreadable medium such as a nonvolatile storage device. Any suitablecomputer readable storage media may be utilized, including hard disks,CD-ROMs, optical storage devices, magnetic storage devices, solid statestorage devices, and/or any combination thereof. In addition, varioustransmission (non-storage) media representing data or events asdescribed herein may be transferred between a source and a destinationin the form of electromagnetic waves traveling through signal-conductingmedia such as metal wires, optical fibers, and/or wireless transmissionmedia (e.g., air and/or space). Various aspects described herein may beembodied as a method, a data processing system, or a computer programproduct. Therefore, various functionalities may be embodied in whole orin part in software, firmware, and/or hardware or hardware equivalentssuch as integrated circuits, field programmable gate arrays (FPGA), andthe like. Particular data structures may be used to more effectivelyimplement one or more aspects described herein, and such data structuresare contemplated within the scope of computer executable instructionsand computer-usable data described herein.

With further reference to FIG. 2, one or more aspects described hereinmay be implemented in a remote-access environment. FIG. 2 depicts anexample system architecture including a computing device 201 in anillustrative computing environment 200 that may be used according to oneor more illustrative aspects described herein. Computing device 201 maybe used as a server 206 a in a single-server or multi-server desktopvirtualization system (e.g., a remote access or cloud system) and can beconfigured to provide virtual machines for client access devices. Thecomputing device 201 may have a processor 203 for controlling overalloperation of the device 201 and its associated components, including RAM205, ROM 207, Input/Output (I/O) module 209, and memory 215.

I/O module 209 may include a mouse, keypad, touch screen, scanner,optical reader, and/or stylus (or other input device(s)) through which auser of computing device 201 may provide input, and may also include oneor more of a speaker for providing audio output and one or more of avideo display device for providing textual, audiovisual, and/orgraphical output. Software may be stored within memory 215 and/or otherstorage to provide instructions to processor 203 for configuringcomputing device 201 into a special purpose computing device in order toperform various functions as described herein. For example, memory 215may store software used by the computing device 201, such as anoperating system 217, application programs 219, and an associateddatabase 221.

Computing device 201 may operate in a networked environment supportingconnections to one or more remote computers, such as terminals 240 (alsoreferred to as client devices and/or client machines). The terminals 240may be personal computers, mobile devices, laptop computers, tablets, orservers that include many or all of the elements described above withrespect to the computing device 103 or 201. The network connectionsdepicted in FIG. 2 include a local area network (LAN) 225 and a widearea network (WAN) 229, but may also include other networks. When usedin a LAN networking environment, computing device 201 may be connectedto the LAN 225 through a network interface or adapter 223. When used ina WAN networking environment, computing device 201 may include a modemor other wide area network interface 227 for establishing communicationsover the WAN 229, such as computer network 230 (e.g., the Internet). Itwill be appreciated that the network connections shown are illustrativeand other means of establishing a communications link between thecomputers may be used. Computing device 201 and/or terminals 240 mayalso be mobile terminals (e.g., mobile phones, smartphones, personaldigital assistants (PDAs), notebooks, etc.) including various othercomponents, such as a battery, speaker, and antennas (not shown).

Aspects described herein may also be operational with numerous othergeneral purpose or special purpose computing system environments orconfigurations. Examples of other computing systems, environments,and/or configurations that may be suitable for use with aspectsdescribed herein include, but are not limited to, personal computers,server computers, hand-held or laptop devices, multiprocessor systems,microprocessor-based systems, set top boxes, programmable consumerelectronics, network personal computers (PCs), minicomputers, mainframecomputers, distributed computing environments that include any of theabove systems or devices, and the like.

As shown in FIG. 2, one or more client devices 240 may be incommunication with one or more servers 206 a-206 n (generally referredto herein as “server(s) 206”). In one embodiment, the computingenvironment 200 may include a network appliance installed between theserver(s) 206 and client machine(s) 240. The network appliance maymanage client/server connections, and in some cases can load balanceclient connections amongst a plurality of backend servers 206.

The client machine(s) 240 may in some embodiments be referred to as asingle client machine 240 or a single group of client machines 240,while server(s) 206 may be referred to as a single server 206 or asingle group of servers 206. In one embodiment a single client machine240 communicates with more than one server 206, while in anotherembodiment a single server 206 communicates with more than one clientmachine 240. In yet another embodiment, a single client machine 240communicates with a single server 206.

A client machine 240 can, in some embodiments, be referenced by any oneof the following non-exhaustive terms: client machine(s); client(s);client computer(s); client device(s); client computing device(s); localmachine; remote machine; client node(s); endpoint(s); or endpointnode(s). The server 206, in some embodiments, may be referenced by anyone of the following non-exhaustive terms: server(s), local machine;remote machine; server farm(s), or host computing device(s).

In one embodiment, the client machine 240 may be a virtual machine. Thevirtual machine may be any virtual machine, while in some embodimentsthe virtual machine may be any virtual machine managed by a Type 1 orType 2 hypervisor, for example, a hypervisor developed by CitrixSystems, IBM, VMware, or any other hypervisor. In some aspects, thevirtual machine may be managed by a hypervisor, while in other aspectsthe virtual machine may be managed by a hypervisor executing on a server206 or a hypervisor executing on a client 240.

Some embodiments include a client device 240 that displays applicationoutput generated by an application remotely executing on a server 206 orother remotely located machine. In these embodiments, the client device240 may execute a virtual machine receiver program or application todisplay the output in an application window, a browser, or other outputwindow. In one example, the application is a desktop, while in otherexamples the application is an application that generates or presents adesktop. A desktop may include a graphical shell providing a userinterface for an instance of an operating system in which local and/orremote applications can be integrated. Applications, as used herein, areprograms that execute after an instance of an operating system (and,optionally, also the desktop) has been loaded.

The server 206, in some embodiments, uses a remote presentation protocolor other program to send data to a thin-client or remote-displayapplication executing on the client to present display output generatedby an application executing on the server 206. The thin-client orremote-display protocol can be any one of the following non-exhaustivelist of protocols: the Independent Computing Architecture (ICA) protocoldeveloped by Citrix Systems, Inc. of Ft. Lauderdale, Fla.; or the RemoteDesktop Protocol (RDP) manufactured by the Microsoft Corporation ofRedmond, Wash.

A remote computing environment may include more than one server 206a-206 n such that the servers 206 a-206 n are logically grouped togetherinto a server farm 206, for example, in a cloud computing environment.The server farm 206 may include servers 206 that are geographicallydispersed while logically grouped together, or servers 206 that arelocated proximate to each other while logically grouped together.Geographically dispersed servers 206 a-206 n within a server farm 206can, in some embodiments, communicate using a WAN (wide), MAN(metropolitan), or LAN (local), where different geographic regions canbe characterized as: different continents; different regions of acontinent; different countries; different states; different cities;different campuses; different rooms; or any combination of the precedinggeographical locations. In some embodiments the server farm 206 may beadministered as a single entity, while in other embodiments the serverfarm 206 can include multiple server farms.

In some embodiments, a server farm may include servers 206 that executea substantially similar type of operating system platform (e.g.,WINDOWS, UNIX, LINUX, iOS, ANDROID, etc.). In other embodiments, serverfarm 206 may include a first group of one or more servers that execute afirst type of operating system platform, and a second group of one ormore servers that execute a second type of operating system platform.

Server 206 may be configured as any type of server, as needed, e.g., afile server, an application server, a web server, a proxy server, anappliance, a network appliance, a gateway, an application gateway, agateway server, a virtualization server, a deployment server, a SecureSockets Layer (SSL) VPN server, a firewall, a web server, an applicationserver or as a master application server, a server executing an activedirectory, or a server executing an application acceleration programthat provides firewall functionality, application functionality, or loadbalancing functionality. Other server types may also be used.

Some embodiments include a first server 206 a that receives requestsfrom a client machine 240, forwards the request to a second server 206 b(not shown), and responds to the request generated by the client machine240 with a response from the second server 206 b (not shown.) Firstserver 206 a may acquire an enumeration of applications available to theclient machine 240 as well as address information associated with anapplication server 206 hosting an application identified within theenumeration of applications. First server 206 a can then present aresponse to the client's request using a web interface, and communicatedirectly with the client 240 to provide the client 240 with access to anidentified application. One or more clients 240 and/or one or moreservers 206 may transmit data over network 230, e.g., network 101.

FIG. 3 shows a high-level architecture of an illustrative desktopvirtualization system. As shown, the desktop virtualization system maybe single-server or multi-server system, or cloud system, including atleast one virtualization server 301 configured to provide virtualdesktops and/or virtual applications to one or more client accessdevices 240. As used herein, a desktop refers to a graphical environmentor space in which one or more applications may be hosted and/orexecuted. A desktop may include a graphical shell providing a userinterface for an instance of an operating system in which local and/orremote applications can be integrated. Applications may include programsthat execute after an instance of an operating system (and, optionally,also the desktop) has been loaded. Each instance of the operating systemmay be physical (e.g., one operating system per device) or virtual(e.g., many instances of an OS running on a single device). Eachapplication may be executed on a local device, or executed on a remotelylocated device (e.g., remoted).

A computer device 301 may be configured as a virtualization server in avirtualization environment, for example, a single-server, multi-server,or cloud computing environment. Virtualization server 301 illustrated inFIG. 3 can be deployed as and/or implemented by one or more embodimentsof the server 206 illustrated in FIG. 2 or by other known computingdevices. Included in virtualization server 301 is a hardware layer thatcan include one or more physical disks 304, one or more physical devices306, one or more physical processors 308, and one or more physicalmemories 316. In some embodiments, firmware 312 can be stored within amemory element in the physical memory 316 and can be executed by one ormore of the physical processors 308. Virtualization server 301 mayfurther include an operating system 314 that may be stored in a memoryelement in the physical memory 316 and executed by one or more of thephysical processors 308. Still further, a hypervisor 302 may be storedin a memory element in the physical memory 316 and can be executed byone or more of the physical processors 308.

Executing on one or more of the physical processors 308 may be one ormore virtual machines 332A-C (generally 332). Each virtual machine 332may have a virtual disk 326A-C and a virtual processor 328A-C. In someembodiments, a first virtual machine 332A may execute, using a virtualprocessor 328A, a control program 320 that includes a tools stack 324.Control program 320 may be referred to as a control virtual machine,DomO, Domain 0, or other virtual machine used for system administrationand/or control. In some embodiments, one or more virtual machines 332B-Ccan execute, using a virtual processor 328B-C, a guest operating system330A-B.

Virtualization server 301 may include a hardware layer 310 with one ormore pieces of hardware that communicate with the virtualization server301. In some embodiments, the hardware layer 310 can include one or morephysical disks 304, one or more physical devices 306, one or morephysical processors 308, and one or more physical memory 316. Physicalcomponents 304, 306, 308, and 316 may include, for example, any of thecomponents described above. Physical devices 306 may include, forexample, a network interface card, a video card, a keyboard, a mouse, aninput device, a monitor, a display device, speakers, an optical drive, astorage device, a universal serial bus connection, a printer, a scanner,a network element (e.g., router, firewall, network address translator,load balancer, virtual private network (VPN) gateway, Dynamic HostConfiguration Protocol (DHCP) router, etc.), or any device connected toor communicating with virtualization server 301. Physical memory 316 inthe hardware layer 310 may include any type of memory. Physical memory316 may store data, and in some embodiments may store one or moreprograms, or set of executable instructions. FIG. 3 illustrates anembodiment where firmware 312 is stored within the physical memory 316of virtualization server 301. Programs or executable instructions storedin the physical memory 316 can be executed by the one or more processors308 of virtualization server 301.

Virtualization server 301 may also include a hypervisor 302. In someembodiments, hypervisor 302 may be a program executed by processors 308on virtualization server 301 to create and manage any number of virtualmachines 332. Hypervisor 302 may be referred to as a virtual machinemonitor, or platform virtualization software. In some embodiments,hypervisor 302 can be any combination of executable instructions andhardware that monitors virtual machines executing on a computingmachine. Hypervisor 302 may be Type 2 hypervisor, where the hypervisorexecutes within an operating system 314 executing on the virtualizationserver 301. Virtual machines may then execute at a level above thehypervisor 302. In some embodiments, the Type 2 hypervisor may executewithin the context of a user's operating system such that the Type 2hypervisor interacts with the user's operating system. In otherembodiments, one or more virtualization servers 301 in a virtualizationenvironment may instead include a Type 1 hypervisor (not shown). A Type1 hypervisor may execute on the virtualization server 301 by directlyaccessing the hardware and resources within the hardware layer 310. Thatis, while a Type 2 hypervisor 302 accesses system resources through ahost operating system 314, as shown, a Type 1 hypervisor may directlyaccess all system resources without the host operating system 314. AType 1 hypervisor may execute directly on one or more physicalprocessors 308 of virtualization server 301, and may include programdata stored in the physical memory 316.

Hypervisor 302, in some embodiments, can provide virtual resources tooperating systems 330 or control programs 320 executing on virtualmachines 332 in any manner that simulates the operating systems 330 orcontrol programs 320 having direct access to system resources. Systemresources can include, but are not limited to, physical devices 306,physical disks 304, physical processors 308, physical memory 316, andany other component included in hardware layer 310 of the virtualizationserver 301. Hypervisor 302 may be used to emulate virtual hardware,partition physical hardware, virtualize physical hardware, and/orexecute virtual machines that provide access to computing environments.In still other embodiments, hypervisor 302 may control processorscheduling and memory partitioning for a virtual machine 332 executingon virtualization server 301. Hypervisor 302 may include thosemanufactured by VMWare, Inc., of Palo Alto, Calif.; HyperV,VirtualServer or virtual PC hypervisors provided by Microsoft, orothers. In some embodiments, virtualization server 301 may execute ahypervisor 302 that creates a virtual machine platform on which guestoperating systems may execute. In these embodiments, the virtualizationserver 301 may be referred to as a host server. An example of such avirtualization server is the Citrix Hypervisor provided by CitrixSystems, Inc., of Fort Lauderdale, Fla.

Hypervisor 302 may create one or more virtual machines 332B-C (generally332) in which guest operating systems 330 execute. In some embodiments,hypervisor 302 may load a virtual machine image to create a virtualmachine 332. In other embodiments, the hypervisor 302 may execute aguest operating system 330 within virtual machine 332. In still otherembodiments, virtual machine 332 may execute guest operating system 330.

In addition to creating virtual machines 332, hypervisor 302 may controlthe execution of at least one virtual machine 332. In other embodiments,hypervisor 302 may present at least one virtual machine 332 with anabstraction of at least one hardware resource provided by thevirtualization server 301 (e.g., any hardware resource available withinthe hardware layer 310). In other embodiments, hypervisor 302 maycontrol the manner in which virtual machines 332 access physicalprocessors 308 available in virtualization server 301. Controllingaccess to physical processors 308 may include determining whether avirtual machine 332 should have access to a processor 308, and howphysical processor capabilities are presented to the virtual machine332.

As shown in FIG. 3, virtualization server 301 may host or execute one ormore virtual machines 332. A virtual machine 332 is a set of executableinstructions that, when executed by a processor 308, may imitate theoperation of a physical computer such that the virtual machine 332 canexecute programs and processes much like a physical computing device.While FIG. 3 illustrates an embodiment where a virtualization server 301hosts three virtual machines 332, in other embodiments virtualizationserver 301 can host any number of virtual machines 332. Hypervisor 302,in some embodiments, may provide each virtual machine 332 with a uniquevirtual view of the physical hardware, memory, processor, and othersystem resources available to that virtual machine 332. In someembodiments, the unique virtual view can be based on one or more ofvirtual machine permissions, application of a policy engine to one ormore virtual machine identifiers, a user accessing a virtual machine,the applications executing on a virtual machine, networks accessed by avirtual machine, or any other desired criteria. For instance, hypervisor302 may create one or more unsecure virtual machines 332 and one or moresecure virtual machines 332. Unsecure virtual machines 332 may beprevented from accessing resources, hardware, memory locations, andprograms that secure virtual machines 332 may be permitted to access. Inother embodiments, hypervisor 302 may provide each virtual machine 332with a substantially similar virtual view of the physical hardware,memory, processor, and other system resources available to the virtualmachines 332.

Each virtual machine 332 may include a virtual disk 326A-C (generally326) and a virtual processor 328A-C (generally 328.) The virtual disk326, in some embodiments, is a virtualized view of one or more physicaldisks 304 of the virtualization server 301, or a portion of one or morephysical disks 304 of the virtualization server 301. The virtualizedview of the physical disks 304 can be generated, provided, and managedby the hypervisor 302. In some embodiments, hypervisor 302 provides eachvirtual machine 332 with a unique view of the physical disks 304. Thus,in these embodiments, the particular virtual disk 326 included in eachvirtual machine 332 can be unique when compared with the other virtualdisks 326.

A virtual processor 328 can be a virtualized view of one or morephysical processors 308 of the virtualization server 301. In someembodiments, the virtualized view of the physical processors 308 can begenerated, provided, and managed by hypervisor 302. In some embodiments,virtual processor 328 has substantially all of the same characteristicsof at least one physical processor 308. In other embodiments, virtualprocessor 308 provides a modified view of physical processors 308 suchthat at least some of the characteristics of the virtual processor 328are different than the characteristics of the corresponding physicalprocessor 308.

With further reference to FIG. 4, some aspects described herein may beimplemented in a cloud-based environment. FIG. 4 illustrates an exampleof a cloud computing environment (or cloud system) 400. As seen in FIG.4, client computers 411-414 may communicate with a cloud managementserver 410 to access the computing resources (e.g., host servers 403a-403 b (generally referred herein as “host servers 403”), storageresources 404 a-404 b (generally referred herein as “storage resources404”), and network elements 405 a-405 b (generally referred herein as“network resources 405”)) of the cloud system.

Management server 410 may be implemented on one or more physicalservers. The management server 410 may run, for example, Citrix Cloud byCitrix Systems, Inc. of Ft. Lauderdale, Fla., or OPENSTACK, amongothers. Management server 410 may manage various computing resources,including cloud hardware and software resources, for example, hostcomputers 403, data storage devices 404, and networking devices 405. Thecloud hardware and software resources may include private and/or publiccomponents. For example, a cloud may be configured as a private cloud tobe used by one or more particular customers or client computers 411-414and/or over a private network. In other embodiments, public clouds orhybrid public-private clouds may be used by other customers over an openor hybrid networks.

Management server 410 may be configured to provide user interfacesthrough which cloud operators and cloud customers may interact with thecloud system 400. For example, the management server 410 may provide aset of application programming interfaces (APIs) and/or one or morecloud operator console applications (e.g., web-based or standaloneapplications) with user interfaces to allow cloud operators to managethe cloud resources, configure the virtualization layer, manage customeraccounts, and perform other cloud administration tasks. The managementserver 410 also may include a set of APIs and/or one or more customerconsole applications with user interfaces configured to receive cloudcomputing requests from end users via client computers 411-414, forexample, requests to create, modify, or destroy virtual machines withinthe cloud. Client computers 411-414 may connect to management server 410via the Internet or some other communication network, and may requestaccess to one or more of the computing resources managed by managementserver 410. In response to client requests, the management server 410may include a resource manager configured to select and provisionphysical resources in the hardware layer of the cloud system based onthe client requests. For example, the management server 410 andadditional components of the cloud system may be configured toprovision, create, and manage virtual machines and their operatingenvironments (e.g., hypervisors, storage resources, services offered bythe network elements, etc.) for customers at client computers 411-414,over a network (e.g., the Internet), providing customers withcomputational resources, data storage services, networking capabilities,and computer platform and application support. Cloud systems also may beconfigured to provide various specific services, including securitysystems, development environments, user interfaces, and the like.

Certain clients 411-414 may be related, for example, to different clientcomputers creating virtual machines on behalf of the same end user, ordifferent users affiliated with the same company or organization. Inother examples, certain clients 411-414 may be unrelated, such as usersaffiliated with different companies or organizations. For unrelatedclients, information on the virtual machines or storage of any one usermay be hidden from other users.

Referring now to the physical hardware layer of a cloud computingenvironment, availability zones 401-402 (or zones) may refer to acollocated set of physical computing resources. Zones may begeographically separated from other zones in the overall cloud ofcomputing resources. For example, zone 401 may be a first clouddatacenter located in California, and zone 402 may be a second clouddatacenter located in Florida. Management server 410 may be located atone of the availability zones, or at a separate location. Each zone mayinclude an internal network that interfaces with devices that areoutside of the zone, such as the management server 410, through agateway. End users of the cloud (e.g., clients 411-414) might or mightnot be aware of the distinctions between zones. For example, an end usermay request the creation of a virtual machine having a specified amountof memory, processing power, and network capabilities. The managementserver 410 may respond to the user's request and may allocate theresources to create the virtual machine without the user knowing whetherthe virtual machine was created using resources from zone 401 or zone402. In other examples, the cloud system may allow end users to requestthat virtual machines (or other cloud resources) are allocated in aspecific zone or on specific resources 403-405 within a zone.

In this example, each zone 401-402 may include an arrangement of variousphysical hardware components (or computing resources) 403-405, forexample, physical hosting resources (or processing resources), physicalnetwork resources, physical storage resources, switches, and additionalhardware resources that may be used to provide cloud computing servicesto customers. The physical hosting resources in a cloud zone 401-402 mayinclude one or more computer servers 403, such as the virtualizationservers 301 described above, which may be configured to create and hostvirtual machine instances. The physical network resources in a cloudzone 401 or 402 may include one or more network elements 405 (e.g.,network service providers) comprising hardware and/or softwareconfigured to provide a network service to cloud customers, such asfirewalls, network address translators, load balancers, virtual privatenetwork (VPN) gateways, Dynamic Host Configuration Protocol (DHCP)routers, and the like. The storage resources in the cloud zone 401-402may include storage disks (e.g., solid state drives (SSDs), magnetichard disks, etc.) and other storage devices.

The example cloud computing environment shown in FIG. 4 also may includea virtualization layer (e.g., as shown in FIGS. 1-3) with additionalhardware and/or software resources configured to create and managevirtual machines and provide other services to customers using thephysical resources in the cloud. The virtualization layer may includehypervisors, as described above in FIG. 3, along with other componentsto provide network virtualizations, storage virtualizations, etc. Thevirtualization layer may be as a separate layer from the physicalresource layer, or may share some or all of the same hardware and/orsoftware resources with the physical resource layer. For example, thevirtualization layer may include a hypervisor installed in each of thevirtualization servers 403 with the physical computing resources. Knowncloud systems may alternatively be used, e.g., WINDOWS AZURE (MicrosoftCorporation of Redmond Wash.), AMAZON EC2 (Amazon.com Inc. of Seattle,Wash.), IBM BLUE CLOUD (IBM Corporation of Armonk, N.Y.), or others.

Enterprise Mobility Management Architecture

FIG. 5 represents an enterprise mobility technical architecture 500 foruse in a “Bring Your Own Device” (BYOD) environment. The architectureenables a user of a mobile device 502 to both access enterprise orpersonal resources from a mobile device 502 and use the mobile device502 for personal use. The user may access such enterprise resources 504or enterprise services 508 using a mobile device 502 that is purchasedby the user or a mobile device 502 that is provided by the enterprise tothe user. The user may utilize the mobile device 502 for business useonly or for business and personal use. The mobile device 502 may run aniOS operating system, an Android operating system, or the like. Theenterprise may choose to implement policies to manage the mobile device502. The policies may be implemented through a firewall or gateway insuch a way that the mobile device 502 may be identified, secured orsecurity verified, and provided selective or full access to theenterprise resources (e.g., 504 and 508.) The policies may be mobiledevice management policies, mobile application management policies,mobile data management policies, or some combination of mobile device,application, and data management policies. A mobile device 502 that ismanaged through the application of mobile device management policies maybe referred to as an enrolled device.

In some embodiments, the operating system of the mobile device 502 maybe separated into a managed partition 510 and an unmanaged partition512. The managed partition 510 may have policies applied to it to securethe applications running on and data stored in the managed partition510. The applications running on the managed partition 510 may be secureapplications. In other embodiments, all applications may execute inaccordance with a set of one or more policy files received separate fromthe application, and which define one or more security parameters,features, resource restrictions, and/or other access controls that areenforced by the mobile device management system when that application isexecuting on the mobile device 502. By operating in accordance withtheir respective policy file(s), each application may be allowed orrestricted from communications with one or more other applicationsand/or resources, thereby creating a virtual partition. Thus, as usedherein, a partition may refer to a physically partitioned portion ofmemory (physical partition), a logically partitioned portion of memory(logical partition), and/or a virtual partition created as a result ofenforcement of one or more policies and/or policy files across multipleapplications as described herein (virtual partition). Stateddifferently, by enforcing policies on managed applications, thoseapplications may be restricted to only be able to communicate with othermanaged applications and trusted enterprise resources, thereby creatinga virtual partition that is not accessible by unmanaged applications anddevices.

The secure applications may be email applications, web browsingapplications, software-as-a-service (SaaS) access applications, WindowsApplication access applications, and the like. The secure applicationsmay be secure native applications 514, secure remote applications 522executed by a secure application launcher 518, virtualizationapplications 526 executed by a secure application launcher 518, and thelike. The secure native applications 514 may be wrapped by a secureapplication wrapper 520. The secure application wrapper 520 may includeintegrated policies that are executed on the mobile device 502 when thesecure native application 514 is executed on the mobile device 502. Thesecure application wrapper 520 may include meta-data that points thesecure native application 514 running on the mobile device 502 to theresources hosted at the enterprise (e.g., 504 and 508) that the securenative application 514 may require to complete the task requested uponexecution of the secure native application 514. The secure remoteapplications 522 executed by a secure application launcher 518 may beexecuted within the secure application launcher 518. The virtualizationapplications 526 executed by a secure application launcher 518 mayutilize resources on the mobile device 502, at the enterprise resources504, and the like. The resources used on the mobile device 502 by thevirtualization applications 526 executed by a secure applicationlauncher 518 may include user interaction resources, processingresources, and the like. The user interaction resources may be used tocollect and transmit keyboard input, mouse input, camera input, tactileinput, audio input, visual input, gesture input, and the like. Theprocessing resources may be used to present a user interface, processdata received from the enterprise resources 504, and the like. Theresources used at the enterprise resources 504 by the virtualizationapplications 526 executed by a secure application launcher 518 mayinclude user interface generation resources, processing resources, andthe like. The user interface generation resources may be used toassemble a user interface, modify a user interface, refresh a userinterface, and the like. The processing resources may be used to createinformation, read information, update information, delete information,and the like. For example, the virtualization application 526 may recorduser interactions associated with a graphical user interface (GUI) andcommunicate them to a server application where the server applicationwill use the user interaction data as an input to the applicationoperating on the server. In such an arrangement, an enterprise may electto maintain the application on the server side as well as data, files,etc. associated with the application. While an enterprise may elect to“mobilize” some applications in accordance with the principles herein bysecuring them for deployment on the mobile device 502, this arrangementmay also be elected for certain applications. For example, while someapplications may be secured for use on the mobile device 502, othersmight not be prepared or appropriate for deployment on the mobile device502 so the enterprise may elect to provide the mobile user access to theunprepared applications through virtualization techniques. As anotherexample, the enterprise may have large complex applications with largeand complex data sets (e.g., material resource planning applications)where it would be very difficult, or otherwise undesirable, to customizethe application for the mobile device 502 so the enterprise may elect toprovide access to the application through virtualization techniques. Asyet another example, the enterprise may have an application thatmaintains highly secured data (e.g., human resources data, customerdata, engineering data) that may be deemed by the enterprise as toosensitive for even the secured mobile environment so the enterprise mayelect to use virtualization techniques to permit mobile access to suchapplications and data. An enterprise may elect to provide both fullysecured and fully functional applications on the mobile device 502 aswell as a virtualization application 526 to allow access to applicationsthat are deemed more properly operated on the server side. In anembodiment, the virtualization application 526 may store some data,files, etc. on the mobile device 502 in one of the secure storagelocations. An enterprise, for example, may elect to allow certaininformation to be stored on the mobile device 502 while not permittingother information.

In connection with the virtualization application 526, as describedherein, the mobile device 502 may have a virtualization application 526that is designed to present GUIs and then record user interactions withthe GUI. The virtualization application 526 may communicate the userinteractions to the server side to be used by the server sideapplication as user interactions with the application. In response, theapplication on the server side may transmit back to the mobile device502 a new GUI. For example, the new GUI may be a static page, a dynamicpage, an animation, or the like, thereby providing access to remotelylocated resources.

The secure applications 514 may access data stored in a secure datacontainer 528 in the managed partition 510 of the mobile device 502. Thedata secured in the secure data container may be accessed by the securenative applications 514, secure remote applications 522 executed by asecure application launcher 518, virtualization applications 526executed by a secure application launcher 518, and the like. The datastored in the secure data container 528 may include files, databases,and the like. The data stored in the secure data container 528 mayinclude data restricted to a specific secure application 530, sharedamong secure applications 532, and the like. Data restricted to a secureapplication may include secure general data 534 and highly secure data538. Secure general data may use a strong form of encryption such asAdvanced Encryption Standard (AES) 128-bit encryption or the like, whilehighly secure data 538 may use a very strong form of encryption such asAES 256-bit encryption. Data stored in the secure data container 528 maybe deleted from the mobile device 502 upon receipt of a command from thedevice manager 524. The secure applications (e.g., 514, 522, and 526)may have a dual-mode option 540. The dual mode option 540 may presentthe user with an option to operate the secured application in anunsecured or unmanaged mode. In an unsecured or unmanaged mode, thesecure applications may access data stored in an unsecured datacontainer 542 on the unmanaged partition 512 of the mobile device 502.The data stored in an unsecured data container may be personal data 544.The data stored in an unsecured data container 542 may also be accessedby unsecured applications 546 that are running on the unmanagedpartition 512 of the mobile device 502. The data stored in an unsecureddata container 542 may remain on the mobile device 502 when the datastored in the secure data container 528 is deleted from the mobiledevice 502. An enterprise may want to delete from the mobile device 502selected or all data, files, and/or applications owned, licensed orcontrolled by the enterprise (enterprise data) while leaving orotherwise preserving personal data, files, and/or applications owned,licensed or controlled by the user (personal data). This operation maybe referred to as a selective wipe. With the enterprise and personaldata arranged in accordance to the aspects described herein, anenterprise may perform a selective wipe.

The mobile device 502 may connect to enterprise resources 504 andenterprise services 508 at an enterprise, to the public Internet 548,and the like. The mobile device 502 may connect to enterprise resources504 and enterprise services 508 through virtual private networkconnections. The virtual private network connections, also referred toas microVPN or application-specific VPN, may be specific to particularapplications (as illustrated by microVPNs 550, particular devices,particular secured areas on the mobile device (as illustrated by O/S VPN552), and the like. For example, each of the wrapped applications in thesecured area of the mobile device 502 may access enterprise resourcesthrough an application specific VPN such that access to the VPN would begranted based on attributes associated with the application, possibly inconjunction with user or device attribute information. The virtualprivate network connections may carry Microsoft Exchange traffic,Microsoft Active Directory traffic, HyperText Transfer Protocol (HTTP)traffic, HyperText Transfer Protocol Secure (HTTPS) traffic, applicationmanagement traffic, and the like. The virtual private networkconnections may support and enable single-sign-on authenticationprocesses 554. The single-sign-on processes may allow a user to providea single set of authentication credentials, which are then verified byan authentication service 558. The authentication service 558 may thengrant to the user access to multiple enterprise resources 504, withoutrequiring the user to provide authentication credentials to eachindividual enterprise resource 504.

The virtual private network connections may be established and managedby an access gateway 560. The access gateway 560 may include performanceenhancement features that manage, accelerate, and improve the deliveryof enterprise resources 504 to the mobile device 502. The access gateway560 may also re-route traffic from the mobile device 502 to the publicInternet 548, enabling the mobile device 502 to access publiclyavailable and unsecured applications that run on the public Internet548. The mobile device 502 may connect to the access gateway via atransport network 562. The transport network 562 may use one or moretransport protocols and may be a wired network, wireless network, cloudnetwork, local area network, metropolitan area network, wide areanetwork, public network, private network, and the like.

The enterprise resources 504 may include email servers, file sharingservers, SaaS applications, Web application servers, Windows applicationservers, and the like. Email servers may include Exchange servers, LotusNotes servers, and the like. File sharing servers may include ShareFileservers, and the like. SaaS applications may include Salesforce, and thelike. Windows application servers may include any application serverthat is built to provide applications that are intended to run on alocal Windows operating system, and the like. The enterprise resources504 may be premise-based resources, cloud-based resources, and the like.The enterprise resources 504 may be accessed by the mobile device 502directly or through the access gateway 560. The enterprise resources 504may be accessed by the mobile device 502 via the transport network 562.

The enterprise services 508 may include authentication services 558,threat detection services 564, device manager services 524, file sharingservices 568, policy manager services 570, social integration services572, application controller services 574, and the like. Authenticationservices 558 may include user authentication services, deviceauthentication services, application authentication services, dataauthentication services, and the like. Authentication services 558 mayuse certificates. The certificates may be stored on the mobile device502, by the enterprise resources 504, and the like. The certificatesstored on the mobile device 502 may be stored in an encrypted locationon the mobile device 502, the certificate may be temporarily stored onthe mobile device 502 for use at the time of authentication, and thelike. Threat detection services 564 may include intrusion detectionservices, unauthorized access attempt detection services, and the like.Unauthorized access attempt detection services may include unauthorizedattempts to access devices, applications, data, and the like. Devicemanagement services 524 may include configuration, provisioning,security, support, monitoring, reporting, and decommissioning services.File sharing services 568 may include file management services, filestorage services, file collaboration services, and the like. Policymanager services 570 may include device policy manager services,application policy manager services, data policy manager services, andthe like. Social integration services 572 may include contactintegration services, collaboration services, integration with socialnetworks such as Facebook, Twitter, and LinkedIn, and the like.Application controller services 574 may include management services,provisioning services, deployment services, assignment services,revocation services, wrapping services, and the like.

The enterprise mobility technical architecture 500 may include anapplication store 578. The application store 578 may include unwrappedapplications 580, pre-wrapped applications 582, and the like.Applications may be populated in the application store 578 from theapplication controller 574. The application store 578 may be accessed bythe mobile device 502 through the access gateway 560, through the publicInternet 548, or the like. The application store 578 may be providedwith an intuitive and easy to use user interface.

A software development kit 584 may provide a user the capability tosecure applications selected by the user by wrapping the application asdescribed previously in this description. An application that has beenwrapped using the software development kit 584 may then be madeavailable to the mobile device 502 by populating it in the applicationstore 578 using the application controller 574.

The enterprise mobility technical architecture 500 may include amanagement and Analytics Service 588. The management and analyticsservice 588 may provide information related to how resources are used,how often resources are used, and the like. Resources may includedevices, applications, data, and the like. How resources are used mayinclude which devices download which applications, which applicationsaccess which data, and the like. How often resources are used mayinclude how often an application has been downloaded, how many times aspecific set of data has been accessed by an application, and the like.

Analytics Service

FIG. 6 shows the Management and Analytics Service 588 that may generateinformation related to how resources (e.g., computing resources, hostingresources, processing resources, network resources, storage resources,hardware resources, software resources, enterprise resources, personalresources, etc.) are used, how often resources are used, and the like.Additionally, Management and Analytics Service 588 may also generateinformation related to network-related events, such as the number andquality of user sessions, connection failures, round trip times, logondurations, and the like. As will be discussed in greater detail below,the information related to network-related events may be displayed to auser or administrator to help troubleshoot network-related problems.Alternatively, the information related to network-related events maytrigger an abnormal condition that prompts the system to take correctiveaction to remediate the abnormal condition.

As illustrated, Management and Analytics Service 588 may be executed onand/or otherwise located on a server (not shown), such as server 206,and may include an input interface 610, Analytics Engine 620, a firstmemory 630, and a second memory 640. Input interface 610 may be any ofthe networking interfaces discussed above. Additionally, input interface610 may be configured to establish communications over a network (notshown) with one or more input sources, such as server 206,virtualization server 301, management server 410, or watchdog 605. Inthis regard, the one or more input sources may provide network events toManagement and Analytics Service 588 via input interface 610. Server206, virtualization server 301, management server 410 may includesoftware, hardware, firmware, or any combination thereof that may beconfigured to provide network events to Management and Analytics Service588. Alternatively, watchdog 605 may be installed on server 206,virtualization server 301, management server 410 to provide networkevents to Management and Analytics Service 588. Watchdog 605 may besoftware, hardware, firmware, or any combination thereof that may beconfigured monitor network events and provide the information relatedthereto to Management and Analytics Service 588. While only one watchdogis illustrated in FIG. 6, any number of watchdogs may be deployedthroughout a networking environment.

Once information related to network events is obtained, the informationmay be passed to Analytics Engine 620. Analytics Engine 620 may besoftware, hardware, firmware, or any combination thereof that may beconfigured to parse the network events received from the one or moreinput sources. Analytics Engine 620 may cause the network events to bedisplayed to one or more users. In order to process the network events,Analytics Engine 620 may include stream processing module 621,interprocess message queue 625, and batch processing module 627. In dataanalytics parlance, stream processing module 621 may be referred to as aspeed layer, interprocess message queue 625 may be referred to as aquery layer, and batch processing module 627 may be referred to as abatch layer. In some embodiments, Analytics Engine 620 may be a singlecode base that implements a single processing pipeline using streamprocessing module 621, interprocess message queue 625, and batchprocessing module 627. Typical systems, such as A-architecture,implement a speed layer, a batch layer, and a query layer. The speedlayer and the batch layer are different codes bases that operate on thesame stream of data, in parallel, via dual pipelines. The speed layermay process data in real-time, the batch layer may handle largequantities of data, and the query layer may output data from the batchlayer and the speed layer. In practice, the speed layer and the batchlayer should produce the same results via the different paths. WhileA-architecture may be useful for providing analytics, its inherentcomplexity from maintaining separate code bases for the speed layer andthe batch layer has limited its influence.

In contrast, the present application describes combining streamprocessing module 621, interprocess message queue 625, and batchprocessing module 627 in a single processing pipeline, as a function ofa single code base, to provide an advantage over prior art systems, likeA-architecture, that divide the processing across multiple pipelines andspread the functionality of these components across multiple code bases.The single processing pipeline described herein may process data inseries instead of parallel. As noted above, typical systems execute thespeed layer and the batch layer in parallel through two different paths.The single processing pipeline disclosed herein may execute the speedlayer (i.e. stream processing) and the batch layer (i.e. batchprocessing) in series. Utilizing a single processing pipeline, derivedfrom a single code base, reduces the complexity of maintaining multiplecode bases and presents a more cost effective solution than prior artsystems. Moreover, the single processing pipeline ensures that streamprocessing module and batch processing module analyze the stream of datato produce the same outcomes based on the analysis performed by thestream processing module and batch processing module. Furthermore, thesingle processing pipeline and single code base provide betterscalability than prior art systems that implement multiple code basesand multiple processing pipelines. In particular, the single processingpipeline and single code base allow for a reduced consumption ofprocessing resources and network bandwidth resources than prior artsystems that implement multiple code bases and multiple processingpipelines.

The single processing pipeline may begin with stream processing module621. Stream processing module 621 may be configured to receive thenetwork events and parse the information contained therein to generatean intermediate result as discussed in greater detail below with respectto FIG. 7. An intermediate result may represent a real-time, or nearreal-time, status of a network event. Near real-time, as used herein,may be any suitable short-time interval, such as one minute, fiveminutes, ten minutes, etc. Accordingly, the intermediate result mayindicate a network event over a time interval. In some embodiments, theintermediate result may represent an average of the network eventbetween a first time (i.e. T_(n-1)) and a second time (T_(n)). Aftergenerating the intermediate result, stream processing module 621 maycause the intermediate result to be displayed via real-time view 623.Additionally, stream processing module 621 may store the intermediateresult in first memory 630. First memory 630 may be a distributed filesystem that is capable of storing a plurality of intermediate results631 received from stream processing module 621 and transferring theplurality of intermediate results 631 to batch processing module 627.Using a distributed file system may allow the analytics capabilitiesdescribed herein to scale more effectively. Alternatively, first memory630 may be any suitable network-based file system capable of scalingeffectively. In yet further embodiments, first memory 630 may be anysuitable storage system, such as a Storage Area Network (SAN).

Next in the single processing pipeline is interprocess messaging queue625. Interprocess messaging queue 625 may transfer instructions and databetween stream processing module 621 and batch processing module 627.For example, interprocess messaging queue 625 may provide a notificationto batch processing module 627 to generate a historical view dataset atregular intervals, such as every hour, once a week, once a month, once ayear, or the like. Alternatively, interprocess messaging queue 625 mayprovide notification to batch processing module 627 that a user hasrequested a custom historical view. For example, the custom historicalview may be a timeframe defined by the user. Additionally, interprocessmessaging queue 625 may provide the information needed to generate thehistorical view dataset. In some embodiments, interprocess messagingqueue 625 may transfer a plurality of intermediate results from streamprocessing module 621 to batch processing module 627. In otherembodiments, interprocess messaging queue 625 may cause a plurality ofintermediate results to be transferred from first memory 630 to batchprocessing module 627. In further embodiments, interprocess messagingqueue 625 may transfer a first plurality of intermediate results fromstream processing module 621 and a second plurality of intermediateresults to be transferred from first memory 630 to batch processingmodule 627

The single processing pipeline may conclude at batch processing module627. Batch processing module 627 may be configured to process aplurality of intermediate results to generate batch data. The batch datamay represent a historical view dataset that corresponds to a predefinedtime interval, such as one hour, one week, one month, or one year.Alternatively, the historical view dataset may be a custom time intervaldefined by a user. Based on the requested time interval, batchprocessing module 627 may obtain a plurality of intermediate resultsfrom first memory 630. The plurality of intermediate results 631obtained from first memory 630 may be associated with the requested timeinterval for the historical view dataset. Batch processing module 627may generate the batch data from the plurality of intermediate results631. Once generated, batch processing module 627 may cause the batchdata and/or historical view dataset to be displayed via historical view629. Causing the historical view dataset to be displayed may includegenerating a visual representation from the historical view dataset.Additionally, batch processing module 627 may store the historical viewdataset in second memory 640. In this regard, second memory 640 may be adatabase, such as a temporal database, that is capable of storing aplurality of historical view datasets.

Turning to FIGS. 7A-7C, an algorithm 700 of how the single processingpipeline operates is shown. Algorithm 700 begins in block 702 with afirst server, running Analytics Engine 620, receiving a stream of data.The stream of data may comprise one or more network events received, viainput interface 610, from the one or more input sources discussed above.In some embodiments, the stream of data may comprise one or more networkevents represented as serialized data. In block 704, the stream of datamay be processed to obtain first intermediate result that represents anetwork event. In some embodiments, stream processing module 621 mayprocess the stream of data to obtain the first intermediate result.Obtaining a first intermediate result may comprise parsing the stream ofdata to obtain plurality of intermediate results 631. Parsing the streamof data may include deserializing the stream of data according to aschema. The schema may be defined by the input source, Analytics Engine620, or any combination thereof, and may define the data types andprotocols present in the stream of data. A first intermediate result maybe selected from the plurality of intermediate results 631 obtained fromparsing the stream of data. In block 706, the first intermediate resultmay be stored in first memory 630. As noted above, first memory 630 maybe a distributed file system that is capable of storing the plurality ofintermediate results 631 received from stream processing module 621. Thedistributed file system described herein may allow the analyticscapabilities to scale more effectively. In block 708, the first serverand, in particular, the stream processing module, may cause the firstintermediate result to be displayed. For example, the first intermediateresult may be displayed as a data point in a real-time view.Additionally, the first intermediate result may be displayed on thefirst server. Alternatively, the first intermediate result may betransmitted over a network and displayed on another server or a userdevice.

In some embodiments, the first intermediate result may be transmitted toa network monitoring system, which may occur concurrently with or priorto blocks 706 and 708. The network monitoring system may be configuredto detect abnormal conditions. FIG. 7B illustrates an exemplaryalgorithm of evaluating the first intermediate result to detect anabnormal condition. In block 720, the first intermediate result may bereceived at a network monitoring system from the first server. In block722, the first intermediate result may be compared to a first thresholdvalue. For example, the first threshold value may be an expected rangefor the first intermediate result. The first intermediate value may becompared to an expected range. For instance, the expected range maycorrespond to a range of acceptable roundtrip times. In another example,the first threshold value may be a limit, such as the number of usersessions or logon duration. In this regard, a limit may be set on thenumber of user sessions due to network condition degradation when thelimit on the number of user sessions is exceeded. In another instance,logon duration may be limited to a number of hours. Alternatively, logonduration may be limited to a range of hours (i.e. 8:00 am through 6:00pm). In block 724, the network monitoring system may determine whetherthe first intermediate result is greater than or equal to a firstthreshold. When the first intermediate result is less than thethreshold, the first intermediate result may be acceptable. Continuingthe examples above, the first intermediate value may be within theexpected range of roundtrip times. Similarly, the number of usersessions or logon durations may be below the acceptable limit. These mayindicate optimal network conditions. Accordingly, the networkconditions, and the first intermediate value, may be provided to amachine learning system to build a first model of the network in block726. In this regard, one or more components of the network may bedetermined via one or more network discovery tools. After the one ormore components are known, the network conditions and the plurality ofintermediate values that satisfy the first threshold value may beprocessed to determine an optimal network configuration. Processing thenetwork conditions and the plurality of intermediate values may includeproviding the network conditions and the plurality of intermediatevalues to a machine learning model, such as a neural network, astraining data. The training data may be used to determine an optimizednetwork configuration based on the network conditions and the pluralityof intermediate values. Subsequent network conditions and intermediatevalues may be compared to the optimized network configuration to detectone or more abnormal conditions. Alternatively, or additionally, thefirst intermediate result may be processed in accordance with steps 706,708, and 710, set forth in FIG. 7A. When the first intermediate resultis greater than or equal to the threshold, an administrator may benotified of the abnormal condition in block 728. Notification mayinclude sending an alert to the administrator, either via email, text,or both. Additionally, notification may include setting a flag on anadministrator's console. In block 730, the network monitoring system mayadjust one or more network parameters to correct the abnormal condition.For instance, when the number of user sessions is equal to or greaterthan the first threshold value, desktop virtualization system mayprovide additional virtual machines for client devices to access. Inresponse to the additional virtual machines being made available forclient devices, the first threshold for the number of user sessions maybe increased. When the number of user sessions subsequently drops, thefirst threshold may be lowered. In another example, additional virtualmachines may be made available when the logon durations are equal to orgreater than the first threshold value. Alternatively, or additionally,client devices may have their connections severed when the logonduration is equal to or greater than the first threshold.

Returning to FIG. 7A, first server may obtain a plurality ofintermediate results from the first memory in block 710. As discussedabove, batch processing module 627 may obtain the plurality ofintermediate results from the first memory at time intervals (e.g. apredetermined or dynamic time interval). Alternatively, batch processingmodule 627 may obtain the plurality of intermediate results from thefirst memory in response to a prompt from interprocess messaging queue625. In block 712, the first server, executing batch processing module627, may process the plurality of intermediate results to produce ahistorical view dataset. As will be discussed in greater detail below,batch processing module 627 may generate the historical view datasetfrom previous historical view datasets. Additionally, or alternatively,batch processing module 627 may use a combination of the plurality ofintermediate results and previous historical view datasets to generatethe historical view dataset. For example, a user may request ahistorical view for the past month. Batch processing module 627 may haveprepared a first historical view for a first week, a second historicalview for the second week, and a third historical view of a third week,but the fourth week has yet to be processed by batch processing module627. The fourth week may constitute a plurality of intermediate resultsin first memory 630. Alternatively, the fourth week may constitute sixdaily historical views in second memory 640 and a day's worth ofplurality of intermediate results in first memory 630. Regardless ofwhere the data is located, batch processing module 627 may use acombination of the plurality of intermediate results and previoushistorical view datasets to generate an up-to-date historical viewdataset based on the most recent datasets.

In block 714, the first server may store the historical view dataset ina second memory, such as a temporal database. In block 716, the firstserver may generate a visual representation of the historical viewdataset. According to some embodiments, generating the visualrepresentation may include processing the historical view dataset usinga database to generate the visual representation. In block 718, thefirst server may cause the visual representation of the historical viewdataset to be presented. Like the first intermediate result discussedabove, the visual representation of the historical view dataset may bedisplayed on the first server or transmitted over a network anddisplayed on another server or a user device.

Additionally, the historical view dataset may also be transmitted to anetwork monitoring system to determine abnormal network events. FIG. 7Cillustrates an algorithm for evaluating whether the historical viewdataset indicates one or more abnormal network conditions. In someembodiments, the algorithm illustrated in FIG. 7C may occur concurrentlywith blocks 714, 716, and 718.

Turning to FIG. 7C, a network monitoring system may receive thehistorical view dataset in block 732. In block 734, the historical viewdataset may be compared to a second threshold value. Similar to thefirst threshold value above, the second threshold value may be ahistorical range to which the historical view dataset is compared. Forexample, the historical range may be roundtrip times, number of usersessions, or logon durations during a preceding interval (i.e., 1 week,1 month, 1 year). Alternatively, or additionally, the historical rangemay be a chart over the preceding interval. In this regard, thehistorical view dataset may be compared to the historical range. In someembodiments, the comparison may detect trending data. For instance, ifthe number of user sessions has been trending up over the precedinginterval, the system may notify an administrator and/or provideadditional virtual machines to handle the increased number of usersessions. The system may take similar action if the duration of logonsappears to be trending upward. In block 736, the network monitoringsystem may determine whether the historical view dataset is greater thanor equal to the second threshold. In this regard, the second thresholdmay indicate a point where additional resource may be allocated toaccommodate additional users. This may be due to a spike in one or morenetwork events. Alternatively, or additionally, crossing the secondthreshold may be the culmination of the historical range trendingupward. When the historical view dataset is less than the threshold, thehistorical view dataset may be provided to a machine learning system asan input for the first model of the network in block 738. Similar to theplurality of intermediate results, the historical view dataset may beprovided as input for the first model to determine an optimal networkconfiguration. In this context, historical view dataset may provide amore accurate picture of optimal network conditions. The historical viewdataset provides a larger dataset to the machine learning model. Asdiscussed above, the historical view dataset may be provided as trainingdata initially to determine an optimized network configuration. When thetraining period concludes, subsequent historical datasets may becompared to the optimized network configuration to detect one or moreabnormal conditions. Additionally, or alternatively, the subsequenthistorical datasets may be sued to update the optimized networkconfiguration by detecting and predicting changes in the networkconfiguration. Alternatively, or additionally, the historical viewdataset may be processed in accordance with the steps 714, 716, and 718,set forth above. When the historical view dataset is greater than orequal to the threshold, an administrator may be notified of the abnormalcondition in block 740. Notification may include providing an alert tothe administrator or setting a flag on an administrator's console. Inblock 742, the network monitoring system may adjust one or more networkparameters to correct the abnormal condition. For example, a desktopvirtualization system may allocate more virtual machines for clientdevices to access based on an indication that the number of usersessions exceeds the second threshold value. Similar to the discussionabove, the second threshold value for the number of user sessions may beincreased based on the allocation of additional virtual machines. Inanother example, additional virtual machines may be made available whenthe logon durations are equal to or greater than the first thresholdvalue.

Occasionally, a user may wish to view a historical view that is notsupported by analytics engine 620. That is, the user may request ahistorical view for a time interval that batch processing module has notprepared. When requests like these are received, stream processingmodule 621 and batch processing module 627 may coordinate to generatethe historical view for the requested time interval. FIG. 8 illustratesan algorithm 800 for generating a historical view based on a requestfrom a user.

Algorithm 800 begins in block 810 with the first server receiving arequest for a second historical view. In some embodiments, the requestmay be received by the stream processing module. The second historicalview may be for a user-defined interval, such as the previous two weeksor prior twenty-one days. Alternatively, the user-defined interval mayspecify a date range. In block 820, the first server may determine thatthe requested second historical view comprises a plurality of historicalview datasets. For example, if the prior twenty-one days are requested,the first server may determine that a third historical view dataset thatcorresponds to the first week, a fourth historical view dataset that isassociated with the second week, and the past weeks' worth ofintermediate results are required to generate the second historicalview. The first server may access second memory 640, which may be atemporal database that stores a plurality of historical view datasetsbased on the time periods to which the historical view datasetcorresponds. For instance, second memory 640 may associate the firstweek with January 6-12 (the first full week of 2019) and the second weekmay be associated with January 13-19 (the second full week of 2019).When the request is made for the prior twenty-one days on January 25th,the first server may determine that the historical view datasets for thetime period between January 6 through January 19 are needed.Accordingly, first server may request the first week (i.e., January6-12) and the second week (i.e., January 13-19) from second memory 640.The most recent week may be obtained from first memory 630.Alternatively, the most recent week may be compiled from dailyhistorical views stored in second memory 640 and the most recent day'sintermediate results from first memory 630. The at least thirdhistorical view dataset and the fourth historical view dataset may thenbe transferred from the second memory to the first memory in block 830.

In block 840, the at least third historical view dataset and the fourthhistorical view dataset may be processed to produce the secondhistorical dataset. In this regard, batch processing module 627 mayretrieve the at least third historical view dataset and the fourthhistorical view dataset from the first memory, and batch processingmodule 627 may process the data to produce the second historical viewdataset, much like batch processing module 627 generates historical viewdatasets from the plurality of intermediate results. In block 850, thefirst server may generate the second historical view from the secondhistorical view dataset. As discussed above, this may include generatingthe second historical view using a database to generate a visualrepresentation. In block 860, the first server may cause the secondhistorical view to be displayed. Like the displays discussed above, thesecond historical view dataset may be displayed on the first server ortransmitted over a network and displayed on an interface on anotherserver or user device. As noted above, historical view datasets may beused to determine trends in the data being monitored and allocateresources based on the determined trends. For instance, the system mayallocate additional virtual machines when the number of user sessionsand/or the duration of logons are trending upward. Similarly, additionalresources may be decommissioned or reallocated for other purposes whenthe historical view datasets trend downward.

While process 800 has been described as providing a user-definedinterval other than those intervals supported by analytics engine (i.e.,12 hours, 1 day, 1 week, 1 month, 1 year), process 800 may also be usedto generate the intervals supported by analytics engine. In this regard,batch processing module 627 may obtain a first 12-hour historical viewdataset and a second 12-hour historical view dataset from the secondmemory, transfer the first 12-hour historical view dataset and thesecond 12-hour historical view dataset to the first memory, and generatea one-day historical view dataset from the first 12-hour historical viewdataset and the second 12-hour historical view dataset. Similarly, theprocess may obtain seven days' worth of historical view datasets andgenerate a one-week historical view dataset. This process may berepeated to generate historical view datasets as necessary.

Turning to FIGS. 9A and 9B, examples of real-time views generated byanalytics engine 620 according to one or more aspects described hereinare shown. Turning to FIG. 9A, real-time view 910 is shown. Real-timeview 910 illustrates a two-hour window of User Sessions. In particular,real-time view 910 shows the timeframe between 7:00 am and 9:00 am, withthe x-axis representing the elapsing time and the y-axis representingthe number of user sessions. Real-time view 910 also shows that theintermediate results may be calculated in three minute intervals. Inthis regard, each of the plurality of intermediate results illustratedin real-time may be data points on the graph, plotted at three minuteintervals. Accordingly, the system may render real-time view 910 fromthe plurality of plotted data points.

Turning back to FIG. 9A, real-time view 910 shows that there were nouser sessions between 7:00 am and 7:30 am. From 7:30 am to 8:00 am,there was one user session, and the number of user sessions continues toincrease until 9:00 am. Real-time view 910 may also present a user withoptions to change the timeframe. In particular, the user may select theprevious 12 hours, the past day, the past week, the past month, and thepast year. Alternatively, timeframes may be presented to the user inreal-time view 910. According to some embodiments, real-time view 910may include an interface for a user to specify a custom timeframe. Usingcustom timeframes may be useful in determining when network conditionsbegan deteriorating. Additionally, custom timeframes may provide insightinto what caused network conditions to deteriorate. While real-time view910 illustrates a bar graph to represent the number of user sessions,any type of visual representation, such as a line graph, may be renderedto illustrate the number of user sessions.

Turning to FIG. 9B, real-time view 920, which illustrates roundtriptimes, is shown. Similar to real-time view 910, real-time view 920 showsa two-hour window between 7:00 am and 9:00 am, with the x-axisrepresenting the elapsing time and the y-axis representing the numberand quality of roundtrip times. Roundtrip times may be used as indicatorof network congestion. Accordingly, real-time view 920 illustrates thenumber and quality of roundtrip times in a stacked bar graph. Forexample, there are five excellent roundtrip times and two fair roundtrip times at 8:00 am. At 9:00 am, system performance appears to degradeas indicated by five fair roundtrip times, in addition to the fiveexcellent roundtrip times. In this example, a network administrator mayinvestigate the cause of the five fair roundtrip times. Additionally, oralternatively, one or more network parameters may be adjusted in attemptto remediate the five fair roundtrip times.

In addition to providing real-time views, analytics engine 620 mayprovide historical views. FIGS. 9A-9C show examples of historical viewsgenerated according to one or more aspects described herein. Turning toFIG. 10A, historical view 1010 is shown and illustrates user sessionsover the past month. Historical view 1010 also shows a first line 1012,illustrating the total number of users, and a second line 1014,illustrating the total number of unique users. First line 1012 maycomprise a plurality of data points; each may correspond to a networkevent, such as the number of total user sessions on a particular day.Similarly, second line 1014 may also comprise a plurality of data pointsto illustrate a network event, such as the total number of unique userson a given day. Historical view 1010 may also include information at thetop of the screen, including the total number of user sessions (i.e.,21), the total number of unique users (i.e., 10), and the number ofsession failures (i.e., 36). Historical view 1010 may depict normalusage, such as a similar number of users Monday through Friday and anexpected dip in usage on weekends. This may be useful in detectingabnormal network conditions. For example, the number of user sessionsbeing low when expected to be high, such as during a work week, may beindicative of network issues that need to be remediated. Accordingly,the system may take steps to resolve the network issues and return tothe expected number of user sessions.

FIG. 10B illustrates an alternative historical view. In particular,historical view 920 illustrates the previous roundtrip times over theprevious month. As discussed above with respect to FIG. 9B, roundtriptimes may be indicative of network congestion or other problems.Accordingly, historical view 1020 may be useful in detecting periodswere roundtrip times degrade. This may provide useful insight to thesystem and/or administrator to determine what may be causing roundtripdelays to perform at unacceptable levels.

Finally, FIG. 10C shows historical view 1030 of logon durations.Historical view 1030 provides an alternative view of a historicaldataset for logon durations. In this regard, historical view 1030includes table 1035 that indicates the number and quality of logons fortwo sites. As illustrated, first site (www.test.com) had eight totallogons, six were excellent, one was fair, and one was poor; second site(www.testl.com) had six total logons, all of which were excellent. Thetotal number of logons may be displayed textually near the top ofhistorical view 1030. In this regard, the information indicates fourteentotal logons, twelve of which were excellent, one was fair, and one waspoor.

The Management and Analytics Service described herein may provide asingle processing pipeline, as a function of a single code base, togenerate real-time and historical views of network events. As discussedabove, the single processing pipeline and single code base providebetter scalability than prior art systems that implement multiple codebases and multiple processing pipelines. In particular, the singleprocessing pipeline and single code base reduces the consumption ofprocessing resources and network bandwidth resources when compared toprior art systems that implement multiple code bases and multipleprocessing pipelines. Accordingly, the single processing pipeline andsingle code base minimizes the complexity of maintaining multiple codebases and presents a more cost effective solution.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are described asexample implementations of the following claims.

What is claimed is:
 1. A method comprising: receiving, by a computingdevice, a stream of data indicative of a plurality of events of anetwork; processing, by the computing device, the stream of data, usinga single processing pipeline, to identify data types and protocolscontained in the stream of data based on a schema defined by an inputsource; generating, using the single processing pipeline, intermediatedata and batch data, the intermediate data being generated from the datatypes and protocols identified in the stream of data and the batch databeing generated from at least a subset of intermediate data thegeneration of the intermediate data and the batch data being done inseries with one another by use of the single processing pipeline;generating, by the computing device, a historical view of the events ofthe network based on the subset of intermediate data and the batch data;and providing, by the computing device, the historical view to anotherprocessing layer to enable the computing device to respond to requestsfor information about the network.
 2. The method of claim 1, comprising:storing, by the computing device, the intermediate data in a firstmemory comprising a plurality of intermediate data.
 3. The method ofclaim 1, comprising: causing, by the computing device, a real-time viewof events occurring on the network to be presented based on theintermediate data, wherein the real-time view of events includes a datapoint corresponding to the intermediate data.
 4. The method of claim 1,comprising: storing, by the computing device, the historical view in atemporal database.
 5. The method of claim 1, wherein the singleprocessing pipeline being executable by a single code base.
 6. Themethod of claim 1, comprising: receiving, by the computing device, arequest for a second historical view of a duration; determining that thesecond historical view comprises a plurality of batch data; obtaining asecond batch data and a third batch data from a first memory; processingthe second batch data and the third batch data to produce the secondhistorical view; and causing the second historical view of the durationto be displayed.
 7. The method of claim 1, comprising: generating analert for an administrator when the intermediate data indicates anabnormal condition.
 8. The method of claim 1, comprising: providing theintermediate data to a machine learning system to build a model of thenetwork.
 9. The method of claim 1, comprising: adjusting one or morenetwork parameters to accommodate additional user devices in response tothe intermediate data.
 10. The method of claim 1, comprising: adjustingone or more network parameters to accommodate additional user devices inresponse to the batch data.
 11. The method of claim 1, whereinprocessing the stream of data to identify data types and protocolscontained in the stream of data further comprises: deserializing thestream of data based on the schema defined by the input source.
 12. Themethod of claim 1, wherein the batch data comprises one or more subsetsof intermediate data for a time interval.
 13. The method of claim 1,wherein the single processing pipeline comprises an interprocess messagequeue.
 14. A computing device, comprising: at least one processor; andmemory storing instructions that, when executed by the at least oneprocessor, cause the computing device to: receive a stream of dataindicative of a plurality of events occurring on a network; process thestream of data, using a single processing pipeline, to identify datatypes and protocols contained in the stream of data based on a schemadefined by an input source; generate, using the single processingpipeline, intermediate data and batch data, the intermediate data beinggenerated from the data types and protocols identified in the stream ofdata and the batch data being generated from at least a subset ofintermediate data the generation of the intermediate data and the batchdata being done in series with one another by use of the singleprocessing pipeline; generate a historical view of the events of thenetwork based on the subset of intermediate data and the batch data; andprovide the historical view to another processing layer to enable thecomputing device to respond to requests for information about thenetwork.
 15. The computing device of claim 14, wherein the memory storesadditional computer-readable instructions that, when executed by the atleast one processor, cause the computing device to: store theintermediate data in a first memory comprising a plurality ofintermediate data.
 16. The computing device of claim 15, wherein thesingle processing pipeline being executable from a single code base. 17.The computing device of claim 14, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, cause the computing device to: cause a real-time view ofevents occurring on the network to be presented based on theintermediate data, wherein the real-time view of events includes a datapoint corresponding to the intermediate data.
 18. The computing deviceof claim 14, wherein the memory stores additional computer-readableinstructions that, when executed by the at least one processor, causethe computing device to: generate an alert for an administrator when theintermediate data indicates an abnormal condition.
 19. The computingdevice of claim 14, wherein the memory stores additionalcomputer-readable instructions that, when executed by the at least oneprocessor, cause the computing device to: provide the intermediate datato a system to build a model of the network.
 20. One or morenon-transitory computer-readable media storing instructions that, whenexecuted by a computing platform comprising at least one processor,memory, and a communication interface, cause the computing platform to:receive a stream of data indicative of a plurality of events occurringon a network; process, using a single processing pipeline, the stream ofdata to identify data types and protocols contained in the stream ofdata based on a schema defined by an input source; generate, using thesingle processing pipeline, intermediate data and batch data, theintermediate data being generated from the data types and protocolsidentified in the stream of data, and the batch data being generatedfrom at least a subset of intermediate data, the generation of theintermediate and the batch data being done in series with one another byuse of the single processing pipeline; generate a historical view of theevents of the network based on the subset of intermediate data and thebatch data; and provide the historical view to another processing layerto enable the computing platform to respond to requests for informationabout the network.
 21. The one or more non-transitory computer-readablemedia of claim 20, wherein the instructions cause the computing platformto: generate an alert for an administrator when the intermediate dataindicates an abnormal condition.
 22. The one or more non-transitorycomputer-readable media of claim 20, wherein the instructions cause thecomputing platform to: adjust one or more network parameters in responseto the intermediate data.